You will get high performance FastAPI backend systems
Rising Talent
Project details
Need a fast and scalable Python backend for your application or AI platform? I build high-performance backend systems using FastAPI with clean architecture and production-ready deployment practices.
Services include:
• REST API development
• Authentication systems
• Async processing
• WebSocket implementation
• AI backend systems
• Database optimization
• Docker deployment
• Microservices architecture
Perfect for startups, AI applications, SaaS products, and enterprise APIs.
Services include:
• REST API development
• Authentication systems
• Async processing
• WebSocket implementation
• AI backend systems
• Database optimization
• Docker deployment
• Microservices architecture
Perfect for startups, AI applications, SaaS products, and enterprise APIs.
Programming Languages
PHP, JavaScript, PythonCoding Expertise
Localization, Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$100
|
Standard
$800
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 1 day | 10 days | 30 days |
Number of Revisions | 1 | 3 | Unlimited |
Number of Pages | 3 | 20 | 50 |
Design Customization | - | ||
Content Upload | - | - | - |
Responsive Design | - | - | - |
Source Code |
About Ahmad
AI Agent & LLM Developer | Laravel Python (FastAPI) SaaS Builder
Semarang, Indonesia - 7:08 am local time
My latest project is a multi-tenant AI SaaS reseller automation platform. FastAPI and React on the frontend, PostgreSQL with pgvector for vector search, Celery and Redis running the background task queue, GPT-4o and DALL·E 3 for generation. It runs several AI agents in a multi agent workflow with a human in the loop checkpoint, and automates a reseller's whole funnel: engaging customers, surfacing products, converting leads.
Before that there's Touchy.ai, a conversational AI character SaaS with GPT-4 chat, voice calls, long-term memory and image generation. Traphyc, a multi-tenant marketing platform with OCR receipt scanning and gamification. Simply Smart Training, an AI sales roleplay LMS running Laravel alongside FastAPI. And SIMTAKA and Stuva, two GIS-based government platforms with multi-step approval workflows and role based access control.
Where I fit best is the stage where a SaaS or marketplace needs a smarter backend but can't afford a rewrite: AI agents that reason over the data instead of guessing, semantic search that understands intent instead of matching keywords, multi-tenant systems built on an API first architecture that hold up as they scale.
A few reasons AI features tend to fall apart in production
-Token spend. If every request fires a fresh AI call with no caching or batching, the bill climbs fast. I run AI work through Celery and Redis so calls get queued and batched through an async backend instead of firing one at a time.
- Output that misses the mark. Letting a model's raw output go straight to a user is a gamble. Every AI agent workflow I've built has a human, or at least a rule, checking the output before it reaches anyone.
- Security gaps in AI-written code. A lot of AI-generated code skips access control entirely. My multi-tenant platforms have role based access control and audit trails from the start, since retrofitting that later is much harder.
- Bolting AI onto the wrong layer. Adding an AI call to an existing stack without rethinking the data layer usually breaks once real traffic hits it. I build the retrieval and orchestration layer first, pgvector and semantic search instead of keyword matching, background task queues instead of synchronous chains, then wire the AI in.
Most of the time, when an AI feature is "working" but expensive or unreliable, the prompt isn't the problem. The architecture underneath it is.
Core Expertise
- AI & Agent Systems: AI agent development with multi agent orchestration and human in the loop checkpoints. Semantic search and RAG using pgvector as a vector database. Conversational AI and chatbot development, GPT-4 chat with memory, voice call simulation. Generative content through GPT-4o and DALL·E 3. Prompt engineering tuned for consistent, cost-aware output.
- SaaS Platform Building: Multi-tenant architecture with real data isolation. Real-time systems using Redis and WebSockets for live dashboards. Subscription billing and invoice automation. Multi-step approval workflows and audit trails. Performance work, query optimization, caching, monitoring, done up front rather than after something breaks.
- Technical Stack: Python and FastAPI for AI agents, REST APIs, and high throughput async backends. Celery for background task queues and microservices. Laravel full-stack, including Filament admin and job queues. PostgreSQL with pgvector, plus MySQL. React, Vue 3, Inertia.js, Tailwind, Pinia on the frontend. GIS work with MapLibre, plus OCR pipelines and government-grade access control.
Recent Projects
- AI SaaS Reseller Automation. FastAPI, React, OpenAI GPT integration. Multi-tenant automation with multiple AI agents, human in the loop checkpoints, pgvector semantic search, and async orchestration through Celery and Redis.
- Touchy.ai. GPT-4 conversational AI with long-term memory, voice call simulation, AI image generation, subscription tiers.
- Traphyc. Multi-tenant marketing platform, landing page builder, OCR receipt scanning, gamified rewards.
- Simply Smart Training. Laravel and FastAPI together, AI sales roleplay simulations, performance tracking.
- SIMTAKA & Stuva. Government GIS platforms, multi-step approval workflows, spatial data validation, role based access control.
- Real-Time Queue Management System. Live dashboards for a government land office, Redis-backed real-time updates, visitor self-registration, reporting.
Your platform works. I can help make it smarter and cheaper to run. Available for new projects now.
Steps for completing your project
After purchasing the project, send requirements so Ahmad can start the project.
Delivery time starts when Ahmad receives requirements from you.
Ahmad works on your project following the steps below.
Revisions may occur after the delivery date.
Brief Explanation
First we will discussed about brief projects, goals, expectation, and milestone about the projects
Analysis
Second, I will plan to map the project, break down tasks, and decide the timeline for the project.